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abstract

Demo: Time Series Online Measurement for Python (TSOMpy)

Published: 17 April 2017 Publication History

Abstract

TSOMpy is a Python library for online measurement of time series, i.e., it provides functions to calculate moving averages, moving histograms, and time-dependent rates. The demo illustrates various methods for these concepts and points out their differences. The tool can be used to apply online measurement to time series randomly generated according to specified stochastic processes or to own data sets. The library furthermore allows the reproduction of the tables and figures presented in [1].

References

[1]
M. Menth and F. Hauser, "On Moving Averages, Histograms and Time-Dependent Rates for Online Measurement," in ACM/SPEC ICPE, 2017.
[2]
----, "TSOMpy -- Time Series Online Measurement in Python," https://www.github.com/uni-tue-kn/TSOMpy, 2017.
[3]
L. Scrucca. (2014, Oct.) Cran: Quality control charts (qcc). {Online}. Available: https://cran.r-project.org/web/packages/qcc/
[4]
N. Developers. (2016, May) Numpy. {Online}. Available: http://www.numpy.org/\BIBentrySTDinterwordspacing
[5]
T. P. D. Team. (2016, Dec.) Python data analysis library. {Online}. Available: http://pandas.pydata.org/
[6]
C. Zhuang. (2016, Nov.) Python package index: Stockstats 0.2.0. {Online}. Available: https://pypi.python.org/pypi/stockstats\
[7]
S. Reifschneider. (2011, Nov.) Github repository: Python-movingaverage. {Online}. Available: https://github.com/linsomniac/python-movingaverage\

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  • (2017)On Moving Averages, Histograms and Time-DependentRates for Online MeasurementProceedings of the 8th ACM/SPEC on International Conference on Performance Engineering10.1145/3030207.3030212(103-114)Online publication date: 17-Apr-2017

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cover image ACM Conferences
ICPE '17: Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering
April 2017
450 pages
ISBN:9781450344043
DOI:10.1145/3030207
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 April 2017

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Author Tags

  1. histograms
  2. moving average
  3. rate measurement

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ICPE '17
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ICPE '17 Paper Acceptance Rate 27 of 83 submissions, 33%;
Overall Acceptance Rate 252 of 851 submissions, 30%

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Cited By

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  • (2017)On Moving Averages, Histograms and Time-DependentRates for Online MeasurementProceedings of the 8th ACM/SPEC on International Conference on Performance Engineering10.1145/3030207.3030212(103-114)Online publication date: 17-Apr-2017

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